Patient-reported Long-term Cosmetic Outcomes Following Short Fractionation Whole Breast Radiotherapy With Boost
Bibliographic record
Abstract
OBJECTIVES: To evaluate the cosmetic effect of a tumor-bed boost after hypofractionated whole breast irradiation (HF-WBI+B) using a patient-reported questionnaire. MATERIALS AND METHODS: Between 2000 and 2005, 4392 women aged 75 years and younger with unilateral early-stage breast cancer received HF-WBI alone or HF-WBI+B. From each group, 800 randomly sampled surviving and nonrelapsed women were invited to complete the Breast Cancer Treatment Outcomes Scale questionnaire. RESULTS: A total of 312 women completed the questionnaire: 154 received HF-WBI alone and 158 received HF-WBI+B. Median ages of respondents were 57 years for HF-WBI alone and 52 years for HF-WBI+B (P<0.001). Women receiving HF-WBI+B had a shorter follow-up interval, higher T stage, higher grade, and were more likely to have had nodal radiotherapy and chemotherapy. There were similar responses comparing the overall appearance of the treated to untreated breast (42% stating no or slight difference for HF-WBI alone vs. 41% for HF-WBI+B, P=0.87). The HF-WBI+B group was: (a) slightly worse on the cosmetic subscale (2.3 vs. 2.1, P=0.02); (b) worse on the pain subscale (2.0 vs. 1.6, P<0.0001); but (c) better on the functional subscale (1.5 vs. 1.8, P<0.001). When the pain subscale was applied to the area around the scar (a surrogate for the tumor-bed), the 2 groups were similar (2.0 vs. 2.0, P=0.71). CONCLUSIONS: Similar to conventional fractionated whole breast radiotherapy with a tumor-bed boost, women who received short fractionation whole breast radiotherapy with boost self-report only slightly worse long-term cosmetic and pain outcomes compared with women who received short fractionation alone.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".